35 citations · 99 across the 6 of their papers we have counts for
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cs.LG2024★ 2 cited
Do Graph Neural Networks Work for High Entropy Alloys?
Hengrui Zhang, Ruishu Huang, Jie Chen +2
Graph neural networks (GNNs) have excelled in predictive modeling for both crystals and molecules, owing to the expressiveness of graph representations. High-entropy alloys (HEAs),…
cs.LG2024★ 3 cited
Adaptive Catalyst Discovery Using Multicriteria Bayesian Optimization with Representation Learning
Jie Chen, Pengfei Ou, Yuxin Chang +4
High-performance catalysts are crucial for sustainable energy conversion and human health. However, the discovery of catalysts faces challenges due to the absence of efficient appr…
cs.LG2023★ 20 cited
MolSets: Molecular Graph Deep Sets Learning for Mixture Property Modeling
Hengrui Zhang, Jie Chen, James M. Rondinelli +1
Recent advances in machine learning (ML) have expedited materials discovery and design. One significant challenge faced in ML for materials is the expansive combinatorial space of…